Detection and Counting of "in vivo" cells to predict cell migratory potential

T. Q. Syed, Vincent Vigneron, S. Lelandais, Georgia Barlovatz-Meimon, Michel Malo, C. Charriere-Bertrand, Christophe Montagne
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引用次数: 6

Abstract

In this paper, we present a work which is performed by biologists and computer scientists both. The aim of this work is to evaluate the migratory potential of cancerous cells. Cancer is characterised by primary tumour. When some cells move they create new tumours, which are called metastases. It is very important to understand this migration process in order to be able to arrest it and increase the chances of a cure. Today, biologists analyse images from different cell cultures and manually count one by one the cells present therein. It is a hard and fastidious work, so here we present some algorithms to automatically perform these tasks of detection and counting. The images that we have are very low contrasted, with a gradient of illumination, and the cells are numerous and tightly aggregated. In this paper different algorithms are evocated and results compared for about 150 images comprising more than 65,000 cells.
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“体内”细胞的检测和计数,以预测细胞的迁移潜力
在本文中,我们提出了一项由生物学家和计算机科学家共同完成的工作。这项工作的目的是评估癌细胞的迁移潜力。癌症以原发肿瘤为特征。当一些细胞移动时,它们会产生新的肿瘤,这被称为转移瘤。了解这种迁移过程是非常重要的,以便能够阻止它并增加治愈的机会。今天,生物学家分析来自不同细胞培养物的图像,并手动逐一计数其中存在的细胞。这是一项艰巨而繁琐的工作,因此我们提出了一些算法来自动执行这些检测和计数任务。我们拥有的图像对比度很低,亮度渐变,细胞数量众多,紧密聚集。本文提出了不同的算法,并对大约150幅包含超过65,000个细胞的图像进行了结果比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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